Apache MXNet (incubating) for Deep Learning

Apache MXNet (incubating) is a deep learning framework designed for both efficiency and flexibility.
It allows you to mixsymbolic and imperative programming
to maximize efficiency and productivity.
At its core, MXNet contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly.
A graph optimization layer on top of that makes symbolic execution fast and memory efficient.
MXNet is portable and lightweight, scaling effectively to multiple GPUs and multiple machines.

MXNet is also more than a deep learning project. It is also a collection of
blue prints and guidelines for building
deep learning systems, and interesting insights of DL systems for hackers.

History

MXNet emerged from a collaboration by the authors of cxxnet, minerva, and purine2. The project reflects what we have learned from the past projects. MXNet combines aspects of each of these projects to achieve flexibility, speed, and memory efficiency.